How the context layer differs
All comparisons
Clinical context layer vs retrieval-augmented generation
A clinical context layer maintains how facts relate to one another over time. Retrieval-augmented generation (RAG) finds fragments similar to a query and hands them to a model, which then has to work out the relationships on every call. The two are complementary, not interchangeable.
ComparisonClinical context layer vs data warehouse
A data warehouse or data lake stores large volumes of data so it can be queried and analysed. A clinical context layer maintains what the facts mean in relation to one another for a patient, right now. A warehouse can be one of the sources a context layer draws on.
ComparisonClinical context layer vs EHR-embedded decision support
Decision support built into the electronic health record typically applies defined rules to recorded data at set points in a workflow. A clinical context layer maintains how facts, including signals outside the record, relate over time. It draws on the record and can feed insight back; it does not replace it.
ComparisonClinical context layer vs general-purpose AI assistant
A general-purpose AI assistant reasons over whatever is placed in its context window for the current conversation. A clinical context layer is the persistent model from which such a window could be drawn. It supplies maintained, scoped context; the assistant, or a clinician, still does the interpreting.
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